The problem of the deficit of time series of phytoproducts is currently partly solved by calculating vegetation indices that provide a multi-temporal spatially continuous picture of the variation of the phytoproduction process. Using the example of the Burtinskaya Steppe site of the Orenburgsky State Nature Reserve, we compiled a functional portrait of the spatio-temporal variability of the phytoproduction process based on a series of 51 Landsat satellite images for the warm period of the 2010‒2020s. A formalized classification based on a set of vegetation indices, transpiration, and reflectivity (albedo) of the vegetation cover has been implemented. We performed a field verification and definition of the syntaxonomic rank of the identified phytocenosis classes. A geomorphological characteristic of ecological niches of phytocenosis classes has been compiled. We established typical types of annual green phytomass, transpiration, and temperature variations for phytocenosis classes, as well as the frequency of deviations from the background functioning mode. Differences in the annual phytoproduction process depend on the degree of relief concavity and the catchment area, an increase in which contributes to the accumulation of snow moisture, a decrease in the rate of its consumption during the warm period, and an extension of the active vegetation period. The annual transpiration and surface temperature variations were more similar for different phytocenosis classes than the annual green phytomass variation. Classification of phytocenoses by the annual course of the phytoproduction process allowed identifying zones of influence of positional factors causing intra-tract differentiation. We managed to clarify the taxonomic affiliation of phytocenoses and landscape boundaries as well. The ratio of xerophilic and mesophilic species indicates the duration of preservation of moisture reserves in the soil and the annual course of phytomass.
Ashikhmin et al. (Wed,) studied this question.